code: def recursive_backtracker(
      maze: np.ndarray, pos: Tuple[int, int]
  ) -> None:
      """
      Recursive backtracker algorithm for maze generation.
  
      Args:
          maze (np.ndarray): The maze represented as a NumPy array.
          pos (Tuple[int, int]): Current position in the maze.
      """
      directions = [(0, 1), (1, 0), (0, -1), (-1, 0)]
      random.shuffle(directions)
      for direction in directions:
          new_pos = pos[0] + direction[0] * 2, pos[1] + direction[1] * 2
          if (
              1 <= new_pos[0] < maze.shape[0] - 1
              and 1 <= new_pos[1] < maze.shape[1] - 1
          ):
              if maze[new_pos] == 1:
                  maze[tuple(np.add(pos, direction))] = 0
                  maze[new_pos] = 0
                  recursive_backtracker(maze, new_pos)
  
file_path: evals/evals/registry/data/mazes/nxn_maze_eval_generator.py
imports: import concurrent.futures
  import json
  import os
  import random
  import threading
  from typing import Dict, List, Tuple, Union
  import networkx
  import numpy
  from numpy import ndarray
  from tqdm import tqdm
label_desc: Use image node_id 1 for calling a global function with example usage: recursive_backtracker(maze, pos) without return types